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Oct 12 · Monday
Another 305 papers do not have category tags yet and are not included in filtered results.
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About this collection Collection in progress We are building a large AI safety paper collection to help researchers find work related to their interests. Papers are collected automatically andfiltered only for relevance to AI safety , without judging quality, novelty or reading value. The default “Annotated first” shows papers with tags or published paper analyses first. Each group is ordered by original publication date, newest first, with undated papers last. “Newest first” uses publication dates only. This order is not a quality ranking.
One-line summaries, tags and paper analyses are prepared by AI from the papers. Language models may have systematic biases and produce hallucinations.We plan to carry out human annotation and review to reduce errors in this content.
揭示推理加深引发的对齐坍塌,用 Reasoning Trap 放大越狱
Published Sep 8
Evaluated models Qwen3-8B , Qwen3-14B , Llama2-7B and others8 Abstract 更深推理提升题目准确率,同时提高扰动下的相对损失。作者研究扩展推理是否以对齐稳健性为代价,提出 ALR、RT 与 RRA。 。
提出 FUSE 框架,评测大语言模型的化生危险能力
Published Sep 2
Evaluated models Claude-3-Haiku , Claude-Opus-4 , Claude-Opus-4.5 and others12 用 TEE-REDBENCH 评测 TEE 顾问的机制幻觉与提示诱导失败
Published Feb 23
Evaluated models ChatGPT-5.2 , Claude Opus-4.6 Abstract 作者用 TEE-REDBENCH 测两款顾问,称失败可迁移且流水线控制可降低发生率。TEE-REDBENCH 红队评测被当作 Intel SGX 与 Arm TrustZone 安全顾问的 ChatGPT-5.2 和 Claude Opus-4.6,看架构推理、远程证明语义、缓解建议和策略约束下的拒答,并测提示诱导失败能否跨助手迁移。作者把助手看成随机策略。
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